When you spend your work life around health IT, every healthcare encounter becomes an opportunity for field research. I find myself studying EHR adoption levels and implementation models during visits to my physicians, or integration shortcomings during hospitalizations, or the state of information exchange when referred for testing.
So when an ill-fated dog walk landed me in the emergency room with a knee injury, I found myself once again in the role of observer.
I’d been treated in this facility several years before, dutifully pre-registering and completing a full medical history. I knew quite well that my record was in the EHR (not one based on InterSystems technology) and confidently handed over my ID and insurance card to the registration clerk.
According to the clerk, I didn’t exist. She carefully entered the relevant data and sent me off to wait my turn to be seen. At that point, I was too confused to think much about it, simply listening impatiently for my name. Once in triage, the implications of my missing identity became more evident as I was called upon to dredge up my entire medical history – the one I knew was already somewhere in that computer system, and was probably also in CRISP, the Maryland state health information exchange (HIE).
I’m generally a pretty clear-headed, logical thinker. But the pain of the fall, which happened at night during a cold rain, had sent me into mild shock. I’d recovered somewhat en route to the hospital, but was hardly at my best during that interview. It was irritating and unnerving. And what if I’d had something more serious than a banged-up knee? What if I were unable to remember critical details?
Just as I completed my rambling recital, my original record mysteriously appeared, in all its coded glory. And during the next four-and-a-half hours of my visit, spent mostly in the waiting room (another field research topic: ED throughput), I had plenty of time to ponder the shortcomings of patient record matching, and the all too common reluctance to leverage the information exchanges in which we have invested so much.
In 1996, I was involved in designing a health data warehouse. We carefully planned for the national patient identifier that would surely be available soon. In 2016, that identifier is still under a congressional ban, ONC has invested countless workgroup hours on patient matching, and CHIME has launched the Herox National Patient ID challenge in an effort to address the issue. In the interim, patients continue to collect unique identifiers from each provider they visit, while organizations merge and combine their patient rosters, implement new EHRs, integrate departmental systems, and do their best to keep everyone straight. Some rely on the master patient index (MPI) in their EHR or revenue cycle management systems. That approach typically results in the kind of encounter I experienced – no match and a frustrated patient.
Some invest countless hours merging and managing records to achieve the same patient-unfriendly results. Other hospitals and health systems are taking an enterprise approach leveraging an independent patient indexsolution.
Investing in better patient identity management capabilities is critical to the success of so many healthcare initiatives. Patient-centric care, population health, accountable care, patient engagement, and value-based reimbursement are all just buzzwords without effective patient matching.
And those of us visiting emergency departments on the receiving end of these capabilities hope that on the next visit, we won’t be nameless strangers.